Automatic set-up for instrument functions

ABSTRACT

Machine-implemented methods and apparatuses to automatically set-up a signal processing system are described. The signal processing system is set to a first bandwidth. A sampling frequency of the signal processing system is set to a first sampling frequency. Next, first samples of first signals are received at the first bandwidth and the first sampling frequency. First parameters of the first signals based on the first samples are determined. Next, a second sampling frequency is determined based on the first parameters to sample second samples. The first parameters of the first signals may be a mean transit time, a minimum transit time, a mean frequency of the signals, and a standard deviation of the frequency of the signals. Next, a mixer frequency is determined based on the first parameters. A low pass filter is set based on the mixer frequency.

FIELD

Embodiments of the invention relate to signal processing systems tocharacterize spherical objects, including particles, droplets, bubbles,and the like. More particularly, embodiments of the invention relate tothe signal processing systems that characterize spherical objects,including particles, droplets, bubbles, and the like, using lightscattering interferometry.

BACKGROUND

Information on size and velocity of spherical objects includingparticles, droplets, bubbles, etc., is important for a wide range ofapplications. These applications include, for example, fuel spraycombustion analysis and control for the automotive industry, aircraftgas turbine combustion, inhaler manufacturing for the pharmaceuticalindustry, household spray systems manufacturing, agricultural pesticideapplication, aircraft icing analysis and control, spray nozzlemanufacturing, atmospheric aerosol analysis, atmospheric studies, andvarious combustion related applications.

Typically, various laser light scattering interferometry techniques areused to determine the size and velocity of spherical objects, such asparticles, drops, bubbles, etc. According to these techniques, sphericalobjects pass the intersection point of two crossed laser beams generatedfrom the same laser. The two crossed laser beams form a sample volume atthe intersection point. The light scattered by the spherical object, asit passes through the sample volume, produces an interference fringepattern at the plane of the detector. The spatial period of theinterference fringe pattern produced by the light scattered from thespherical object, as it passes through the sample volume, may be used todetermine the size of the spherical object and a velocity component ofthe spherical object. The laser light scattering interferometrytechniques may include a laser Doppler velocimetry (“LDV”), a laserDoppler anemometry (“LDA”), a phase Doppler interferometry (“PDI”),phase Doppler particle analyzer technique (“PDPA”), phase Doppleranemometer technique (“PDA”).

The measurements of the size and velocity of the spherical objectsinvolve many parameters that may change over the measurement. Forexample, temporal and spatial characteristics of the flow of thespherical objects may change, e.g., due to changes in droplet sizedistribution, and due to gradients of the flow velocity. In manyapplications, e.g., for gas turbine and automotive fuel sprays, andindustrial spray studies, the number density and velocity of particleschanges dramatically from location to location. The small particle sizeand random attenuation of the scattered light caused by other dropletsthat pass the laser beams close to the sample volume may produce lowsignal to noise ratio.

Generally, the phase shifts of the signals that are produced byphotodetectors are measured to estimate the spatial period of theinterference fringe pattern produced by the light scattered from thespherical objects. The phase shifts may vary with measurementconditions, e.g., signal frequency, gain of the photodetector, and otherinstrument parameters.

These parameters, e.g., varying temporal and spatial characteristics,varying number density of the particles, varying particle speed, lowsignal-to-noise ratio, varying phase shifts, increase measurementuncertainty, cause measurement errors, and impact the measurementaccuracy and reliability. Therefore, the measurements of the size andvelocity of the spherical objects require frequent attention to themeasurement conditions which may be time-consuming and improper setupmay leave the instrument prone to errors.

SUMMARY

Machine-implemented methods and apparatuses to automatically set-up asignal processing system are described. The signal processing systemincludes an instrument for measuring spherical objects. The signalprocessing system is set to a first bandwidth. A sampling frequency ofthe signal processing system is set to a first sampling frequency. Firstsamples of first signals are received at the first bandwidth and thefirst sampling frequency. First parameters of the first signals based onthe first samples are determined. A second sampling frequency isdetermined based on the first parameters to sample second samples. Thefirst parameters of the first signals may be a mean transit time, aminimum transit time, a mean frequency of the signals, and a standarddeviation of the frequency of the signals. A mixer frequency isdetermined based on the first parameters. A low pass filter is set basedon the mixer frequency.

For one embodiment, a gain is set to a first value. The signals arereceived by the signal processing system. Intensities of the receivedsignals are measured. The gain is adjusted to a second value based onthe intensities.

For another embodiment, parameters of spherical objects passing througha first sample volume are determined. A probability that more than onespherical object resides at a time in the first sample volume is lessthan a predetermined threshold is determined based on the parameters ofthe spherical objects. An aperture of the signal processing system isadjusted based on the probability.

For yet another embodiment, samples of the signals are received by thesignal processing system. Parameters of the samples of the signals aredetermined. A relative number of the samples that pass a validationcriterion for each of the parameters is estimated. A measurementuncertainty of the signal processing system is determined based on theestimating.

For yet another embodiment, the signal processing system is calibrated.First signals are received by the signal processing system. Firstparameters of the first signals are determined to characterizecomponents of the system. Next, second signals are received. Secondparameters of the second signals are determined to characterizespherical objects. The second parameters are adjusted based on the firstparameters.

Other features of the present invention will be apparent from theaccompanying drawings and from the detailed description that followsbelow.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention is illustrated by way of example and notlimitation in the figures of the accompanying drawings in which likereferences indicate similar elements.

FIG. 1 shows one embodiment of a system for determining the size andvelocity of spherical objects;

FIG. 2 shows one embodiment of an apparatus for measuring the size andup to three velocity components of a spherical object;

FIG. 3A shows one embodiment of a signal processor to receive andprocess signals to determine the size and one or more of velocitycomponents of spherical objects;

FIG. 3B shows one embodiment of a typical Doppler burst signal beforeand after high-pass filtering in photodetector section;

FIG. 4 shows one embodiment of photodetector section of a signalprocessor to determine the size and one or more velocity components ofthe spherical objects;

FIG. 5 shows one embodiment of an analog section of a signal processorto determine the size and one or more velocity components of thespherical objects;

FIG. 6 shows a block diagram of one embodiment of a signal processor todetermine the size and velocity of spherical objects;

FIG. 7 is a flowchart of one embodiment of a method to automatically setup a signal processing system to determine the sizes and velocities ofthe spherical objects;

FIGS. 8A-8D illustrate embodiments of spectrums of electrical signals;

FIG. 9 shows a flowchart of another embodiment of a method toautomatically set up a signal processing system to determine the sizesand velocities of the spherical objects;

FIG. 10 illustrates one embodiment of a complex signal data in theabsence of noise when the sampling frequency is four times of the inputsignal;

FIG. 11 shows the signal sampled data using two sampling frequenciesaccording to one embodiment of the invention;

FIG. 12 is a flowchart of another embodiment of a method toautomatically set up a signal processing system to determine the sizesand velocities of the spherical objects that includes automaticallyadjusting a gain;

FIG. 13 is a flowchart of one embodiment of a method to automaticallyset up a signal processing system to determine the sizes and velocitiesof the spherical objects that includes automatically adjusting anaperture of the signal processing system;

FIG. 14 is a flowchart of one embodiment of a method to automaticallyset up a signal processing system to determine the sizes and velocitiesof the spherical objects that includes automatically estimating ameasurement uncertainty of the signal processing system for each of themeasured spherical objects;

FIG. 15 is a flowchart of one embodiment of a method to automaticallyset up a signal processing system to determine the sizes and velocitiesof the spherical objects that includes an automated detectorcalibration; and

FIG. 16 illustrates one embodiment of a system to determine the size andvelocity of the spherical objects that automatically sets up forinstrument functions.

DETAILED DESCRIPTION

Machine-implemented methods and apparatuses are described toautomatically set-up a signal processing and optical system to determinesizes and velocities of spherical objects, e.g., particles, drops,bubbles, and the like.

The signal processing system includes a photodetector section to converta light scattered from a spherical object to electrical signals. Thesignal processing system further includes an analog section coupled tothe photodetector section. The analog section has a mixer and a low passfilter. A digital section is coupled to the analog section to sample theelectrical signals.

The signal processing system is a user friendly turnkey system that canbe reliably set up to consistently provide accurate measurements withpredictable measurement uncertainty.

The signal processing system is automatically set to a first bandwidth(e.g., a full processor bandwidth). A sampling frequency of the signalprocessing system is automatically set to a first sampling frequency(e.g., a maximum processor sampling frequency). Next, first samples offirst signals are received at the first bandwidth and the first samplingfrequency. First parameters of the first signals based on the firstsamples are determined. Next, a second sampling frequency is determinedbased on the first parameters to sample second samples. The firstparameters of the first signals may be a mean transit time, a minimumtransit time, a mean frequency of the signals, and a standard deviationof the frequency of the signals. Next, a mixer frequency is determinedbased on the first parameters. A low pass filter is set based on themixer frequency. A decimation factor is set based on the setting of thelow pass filter and the sampling frequency.

For one embodiment, a gain of the photodetector section of the signalprocessing system is set to a first value. The signals are received bythe signal processing system. Next, intensities of the received signalsare measured. The gain is adjusted to a second value based on theintensities, so that a smallest intensity of the signals is higher orequal to a detection level of the system and a largest intensity of thesignals is less or equal to a saturation level of the system.

For another embodiment, parameters of spherical objects passing througha first sample volume are measured. Next, a probability that more thanone spherical object resides at a time in the first sample volume isless than a predetermined threshold is determined based on theparameters of the spherical objects. Next, an aperture in front of thephotodetector section is adjusted based on the probability of more thanone spherical object passing the sample volume at one time.

For yet another embodiment, samples of the signals are received by thesignal processing system. First parameters of the samples onphotodetectors are measured. Next, a first number of the samples thatpass a first parameter validation criterion is estimated. Further,second parameters of the samples of the signals on the photodetectorsare measured. Next, a second number of the samples that pass a secondparameter validation criterion is estimated. Next, a global measurementuncertainty of the signal processing system is determined based on thefirst number and the second number.

For yet another embodiment, the signal processing system is calibrated.First signals are received by the signal processing system from acalibration source. First parameters of the first signals are measuredto characterize components of the system at an operating condition of aplurality of operating conditions. Next, second signals from a sphericalobject are received. Second parameters of the second signals aremeasured to characterize spherical objects. The second parameters areadjusted based on the first parameters. For one embodiment, a look uptable is generated based on the first parameters at each of theplurality of the operating conditions. The second parameters areadjusted based on the look up table.

An automatic setup is configured to measure the frequency response ofthe different components of the system for auto-calibration of thesystem. Next, the automatic setup is configured to automatically set thesystem gain for optimum utilization of the system dynamic range.Further, the automatic setup is configured to minimize the systemmeasurement uncertainty including the use of multiple samplingfrequencies and the use of multiple phase and frequency measurements.

FIG. 1 shows one embodiment of a system for determining the size andvelocity of spherical objects. A system 100 has a transmitter portion101 and a receiver portion 102. Transmitter 101 includes a laser 110that generates a laser beam 111, a beam splitter 120 and a focusingoptics 130. As shown in FIG. 1, laser beam 111 is split by beam splitter120 into two beams 121 of about the same intensity. As shown in FIG. 1,focusing optics 130, e.g., one or more lenses, focuses beams 121 andcauses them to cross each other at an angle 132 to form a sample volume141 having an interference fringe pattern. An enlarged view of oneembodiment of the interference fringe pattern 190 formed by crossingbeams 121 is shown in FIG. 1. Sample volume 141 is an overlap region ofbeams 121 which cross each other at angle 132, as shown in FIG. 1. Forone embodiment, angle 132 depends on the size of measured particle. Forone embodiment, increasing angle 132 increases the difference betweenthe phase of light scattered by refraction and reflection, allowing moreeffective discrimination between refraction and reflection components ofthe scattered light. For one embodiment, angle 132 formed by crossingbeams 121 is in the approximate range of 1 to 20 degrees. For oneembodiment, each of the laser beams 121 at the overlap region has aGaussian or other light intensity profile. For an embodiment, beamsplitter 120 and focusing optics 130 of transmitter 101 are commerciallyavailable optical components known to one of ordinary skill in the artof optical transmitter manufacturing.

As shown in FIG. 1, one of the beams 121 generated by laser 110 ismodulated with a frequency by a modulator 131 to provide frequencyshifting. The frequency shifting is used to compress the frequencydynamic range and resolve the direction ambiguity that would occur forspherical objects passing in a reverse direction. For one embodiment,the frequency of the modulator 131 to modulate one of the laser beams121 is in the approximate range of 20 to 60 Megahertz (“MHz”). For anembodiment, the modulator 131 modulates one of the laser beams 121 is anacousto-optical modulator. For one embodiment, the modulator 131 tomodulate one of the laser beams 121 is a Bragg cell. Bragg cells areknown to one of ordinary skill of optical transmitter manufacturing.

For one embodiment, each of the Gaussian laser beams 121 is firstclipped to remove light on the wings of the Gaussian curve at somedesired level (e.g., I/I_(o)=1/e²) to reduce the size of the samplevolume and decrease the number of signals to be processed that willultimately be rejected in at signal validation operations. Clipping thewings of the Gaussian curve of the laser beams also helps to betterdefine the particle detection region needed in analyzing the results forestimating particle number density and flux.

An optical receiver collecting optics 160 is positioned at an off-axisdetection angle 150 from the transmitted beam direction. For oneembodiment, off-axis detection angle 150 is in the approximate range of20-75 degrees from direction 151 of transmitting beams 121. The lightfrom crossing beams 121 is scattered by spherical objects 140, e.g.,particles, drops, bubbles, and the like, passing through sample volume141 located at the intersection of the beams 121. The light from each ofthe two laser beams 121 scattered from one of the spherical objects 140by various scattering mechanisms, e.g., refraction and reflection,interferes to form a spatially and temporally varying fringe pattern 191on receiver optics 160. The collecting optics 160 of the receiver 102collects the interference fringe pattern formed by the scattered light,partitions the interference fringe pattern into three portions 161, 162and 163, and directs them on to a signal processor 180. Signal processor180 includes a photodetector section 171 and a processing section 170described in further detail below. Photodetector section 171 includesthree spaced apart photodetectors 164, 165 and 166. As shown in FIG. 1,each of the photodetectors 164-166 receives a respective portion 161-163of the interference fringe pattern produced by the light scattered fromone of the spherical objects 140. For one embodiment, the detectors 164,165 and 166 are located in the interference fringe pattern, or an imageof it, and the separation between the detectors 164, 165 and 166 isknown.

When the spherical object, e.g., a particle, drop, bubble, and the like,is moving, a Doppler shift in the frequency of the scattered lightoccurs. The difference in the Doppler frequency shift plus the imposedfrequency shift by the frequency modulator between the light scatteredfrom each of the beams 121 causes the fringe pattern to appear to move.As the interference fringe pattern sweeps past photodetectors 164-166 atthe Doppler difference frequency plus the imposed frequency shift by thefrequency modulator, photodetectors 164-166 produce time varying signals167-168. For one embodiment, when the light received by photodetectors164-166 is scattered from the spherical object due to a single dominantscattering mechanism, e.g, either a refraction, or reflection, theinterference fringe pattern is periodic, e.g., a sinusoidal wave signal.The periodic interference pattern that sweeps past photodetectors164-166 at the Doppler difference frequency produces signals 167-168that are identical in frequency, but shifted in phase. The phase shift φis related to the spacing of the scattered fringe pattern through thefollowing relationship:

$\begin{matrix}{\frac{\varphi}{360{^\circ}} = \frac{s}{\Lambda}} & (1)\end{matrix}$

wherein s is the spacing between a pair of the photodetectors, forexample, photodetectors 161 and 162, φ is the phase shift between thesignals 167 and 168, and Λ is the spacing between the fringes(wavelength) of the interference pattern at the location of thephotodetectors 164 and 165 and is inversely proportional to the diameterof the spherical object.

For one embodiment, the spherical object's size may be in theapproximate range of 0.5 micrometers (“um”) to 1000 um, for example. Tomeasure a velocity component, any one of photodetectors 164, 165, and166 may be used. For one embodiment, a small aperture (not shown) isused in front of the signal processor 180 (e.g., at the rear focal pointof the receiver optics) to allow only light scattered by particlescrossing a small region of the beam intersection to reach thephotodetectors 164-166. The rest of the scattered light is blocked bylight blockers 142 for safety reasons. The small aperture (not shown)may be used in the receiver lens path to minimize the noise in thesignal and limit the size of the measurement volume.

Photodetectors 164, 165, and 166 are used to resolve the phaseambiguity, extend the measurement range and resolution, and to validateeach of the time varying signals 167-169 for determining the size andvelocity of the spherical object. As shown in FIG. 1, photodetectors164-166 send time varying electrical signals 167-169 to processingsection 170 to determine the size and velocity of spherical objects.Signal processor 180 is described in further detail below with respectto FIGS. 3-17.

FIG. 2 shows one embodiment of an apparatus 200 for measuring the sizeand up to three velocity components of a spherical object. Beampropagation with respect to the Cartesian coordinate system 224 is shownin FIG. 2. The apparatus 200 has a transmitter 210 for generating afirst pair of coherent beams 211 propagating along an axis Z in theplane ZY and crossing each other at an angle 212 to form a sample volume213 to measure a size and an Y-velocity component of a spherical objectlocated inside the sample volume 213. The apparatus 200 also has atransmitter 220 that generates a second pair of coherent beams 215propagating a plane ZY along an axis Y that is perpendicular to an axisZ. The beams 215 cross each other at an angle 216 to form sample volume213 to measure a Z-velocity component of the spherical object locatedinside the sample volume 213. The apparatus 200 further includes atransmitter 230 that generates a third pair of coherent beams (notshown) propagating in a plane XY along axis Y. The third pair of thebeams cross each other at an angle to form sample volume 213 to measurean X-velocity component of the spherical object located inside thesample volume 213. For one embodiment, the transmitter 230 is stacked ontop of the 220. For one embodiment, the angles formed by each pair ofcoherent beams 211, 215, and 217 is in the approximate range of 1 degreeto 20 degrees.

For an embodiment, each of the transmitters 210, 220, and 230 is acompact, highly efficient, commercially available diode-pumpedsolid-state (“DPSS”) laser having substantially high pointing stability.For one embodiment, the DPSS laser models GCL-XXX-S, BCL-XXX-S, etc.,supplied by CrystaLaser of Reno, Nev. may be used. More specifically,the pointing stability of the DPSS used in transmitters 210, 220, and230 is less than about 0.02 mrad.

For an embodiment, to simultaneously measure the size and three velocitycomponents of the spherical object, transmitters 210, 220, and 230generate light at a first, a second, and a third wavelength,respectively. More specifically, the first, second, and thirdwavelengths are, for example, violet, red, and green, respectively. Foranother embodiment, each of the transmitters 210, 220, and 230 generatelight having a first, second, and third polarization, respectively. Foryet another embodiment, two transmitters 210 and 220 generate lighthaving a first and second wavelength respectively, with the samepolarization, and the transmitter 230 generates light having the firstwavelength, but the polarization is different from the polarization ofthe transmitters 210 and 220.

For apparatus 200 of FIG. 2, the scattered light 221 from the sphericalobject is collected by a signal processor 240 that is configured tosense the scattered light 221, convert it to time varying electricalsignals, and process the signals as described in further detail belowwith respect to FIGS. 3-17. As shown in FIG. 2, system 200 has avariable aperture 223 in front of signal processor 240. For oneembodiment, variable aperture 223 is a movable strip-like slit aperture.For one embodiment, the strip has a plurality of slit widths atdifferent locations along the strip. For one embodiment, the slit isformed by two movable blades that can be separated at the desired slitwidth. For one embodiment, signal processor 240 includes threephotodetectors, wherein each of the photodetectors receives a portion ofan interference fringe pattern formed by a light scattered from aspherical object and generates a time varying signal to produce aplurality of time varying signals, as described above. For anembodiment, signal processor 240 is positioned off-axis to thetransmitter beams direction. The central axis of the signal processor240 forms an angle 222 relative to a propagation axis of the first pairof beams 211.

For an embodiment, signal processor 240 is positioned off-axis to thetransmitter beams direction. The central axis of the signal processor240 forms an angle 222 relative to a propagation axis of the first pairof beams 211. For an embodiment, the angle 222 is in the approximaterange of 25 to 45 degrees. For one embodiment, the angle 222 is about 30degrees. The signal processor 240 is in a plane that passes through thecrossing of the beams, and is orthogonal to the plane formed by the twocrossing beams.

FIG. 3A shows one embodiment of a signal processor to receive andprocess signals to determine the size and one or more of velocitycomponents of spherical objects. As shown in FIG. 3, signal processor300 includes a photodetector (“PD”) section 301, analog section 302, anddigital section 303. As shown in FIG. 3, optical signals 305 arecollected by receiver optics (not shown) of photodetector section 301,converted to electrical signals and passed to analog section 302. Forone embodiment, the receiver optics are LDV optics, LDA optics, PDIoptics, PDPA optics, PDA optics, or any other optics known to one ofordinary skill in the art of the optics manufacturing. For oneembodiment, the signals received from the spherical objects are Dopplerburst signals. For one embodiment, the amplitude of the signals fromspherical objects can vary over a wide dynamic range (over 1:10,000)from one measurement to another. For one embodiment, the gain of thephotodetector section 301 is changed automatically to fit the signalshaving various amplitudes to a fixed input amplitude range of the signalprocessor.

FIG. 3B shows one embodiment 310 of a typical Doppler burst signalbefore 306 and after 307 high-pass filtering in photodetector section301. As shown in FIG. 3B, Doppler burst signal 306 has an envelope(e.g., a Gaussian shape envelope), amplitude 309, and width 308. Asshown in FIG. 3B, burst signal 306 is modulated by a sinusoidal wave.Optical frequency shifters e.g., Bragg cells, are used to modulate thefrequency of the burst signal. Modulating the burst signal frequency isused to detect the direction of motion of spherical objects, asdescribed above with respect to FIG. 1. Modulating the burst signalfrequency is also used to reduce the relative frequency range of theburst signals. The Doppler frequency shift is determined by the dropletvelocity component in the plane of two crossing laser beams, asdescribed above with respect to FIGS. 1 and 2. The frequencies of thesignal bursts are determined by the sum of the Doppler frequency shiftand the frequency of the optical shifter. The signal frequencies mayvary from about 5 MHz to more than 200 MHz. For one embodiment, theamplitude 309 of the burst signal 306 can vary over a dynamic range ofabout 1:2500. The transit time τ of the signal burst 306 is determinedby the width 308 of the signal burst. The transit time τ of the signalburst 306 determined by the speed v of the spherical object and thediameter w of the focused laser beam at the sample volume according tothe formula:

τ=w/v  (2)

For one embodiment, transit time τ can vary in the approximate rangefrom 10 nanoseconds (“ns”) to more than 10 milliseconds (“msec”).

Referring back to FIG. 3, photodetector section 301 has two outputs.Electrical signals from output X may be used to measure peak intensityand average power to adjust the gain of the photodetector section 301,as described in further detail below with respect to FIGS. 4, 6, and 12.Electrical signals from output Z are fed to analog section 302.

FIG. 4 shows one embodiment 400 of photodetector section 301 of a signalprocessor to determine the size and one or more velocity components ofthe spherical objects.

As shown in FIG. 4, optical signals 401 are received by one or morephotodetectors 402. Photodetectors 402 convert optical signals 401 intoelectrical burst signals 403, e.g., current. As shown in FIG. 4,electrical signals 403 are then fed to a transimpedance amplifier(“TIA”) 404. Transimpedance amplifier 404 is used to convert aphotodetector current to voltage. As shown in FIG. 4, output 405 of TIA404 may be used to measure e.g., an average power of the signal, andpeak intensity of the signal. The peak intensity and the average powerof the signals may be used for adjustment of the gain of one or morephotodetectors 402, as described in further detail below. For oneembodiment, photodetectors 402 are photomultiplier tubes (“PMTs”). Forone embodiment, the gain of photodetector section 301 can be adjusted bychanging the bias high voltage of the PMTs. For another embodiment,photodetectors 402 are fixed gain photodetectors, e.g., PINphotodetectors and avalanche photodetectors (“APD”). For one embodiment,the gain of the fixed gain photodetectors is adjusted by placing one ormore variable optical attenuators (not shown) in front of the one ormore photodetectors 402. As shown in FIG. 4, signals from output 406 ofTIA 404 are filtered by high-pass filter (“HPF”) 407 and thenpre-amplified, e.g., by 15 dB, using pre-amplifier 408. Afterpre-amplifier 408, electrical signals are input to analog section 303.

Referring back to FIG. 3, analog section 303 is used to change thesignal processor frequency bandwidth to fit the actual frequencybandwidth of the input Doppler signals to optimize the signal processorperformance and to maximize the signal-to-noise ratio (“SNR”).

FIG. 5 shows one embodiment 500 of an analog section 303 of a signalprocessor to determine the size and one or more velocity components ofthe spherical objects. As shown in FIG. 5, electrical signals S(t) fromphotodetector section 301 are split and fed to quadrature mixers 501 and502. For one embodiment, electrical signals S(t) are amplified in theanalog section 302 by an amplifier (not shown) before being fed toquadrature mixers 501 and 562 to provide immunity to electromagneticinterference (“EMI”) and ground loops. As shown in FIG. 5, mixer 501 isdriven by a quadrature local oscillator f₀∠90. Mixer 502 is driven by anin-phase local oscillator f₀∠0. The output of mixer 501 is applied toLPF 503 to generate quadrature signals Si(t), and output of mixer 502 isapplied to LPF 504 to generate in-phase signals Sr(t).

Quadrature mixers 501 and 502 and low pass filters 503 and 504 are usedto adjust the frequency bandwidth of the signal processor to an actualinput frequency bandwidth of incoming Doppler signals. For oneembodiment, the actual frequency bandwidth of Doppler signals does notexceed 0.1 of the full bandwidth of the signal processor. For example,the full bandwidth of the signal processor may be more than 100 MHz, andthe actual bandwidth of the Doppler signals may be less than 10 MHz.

Generally, the mixer produces the sum and difference of the signalfrequency and the mixer frequency as shown in the expressions below.

f ⁺=(f _(s) +f _(D))+f _(o)  (3)

f ⁻=(f _(s) +f _(D))−f _(o)  (4)

where the signal frequency is a sum of the optical shifter frequencyf_(s) and the Doppler difference frequency f_(D), and f₀ is the mixerfrequency. As shown in FIG. 5, mixer 501 (or the mixer f_(m) 1) producesthe sum f⁺ and difference f⁻ of the signal frequency and the frequencyf₀ of the mixer 501. Mixer 502 (or the mixer f_(m2)) produces the sum f⁺and difference f⁻ of the signal frequency and mixer frequency f₀ (whichhas the same frequency f₀ of the mixer 501 at a quadrature or 90 degreesphase shift), as shown in FIG. 5. The sum frequency f⁺ of the mixer isremoved by a respective low pass filter. As shown in FIG. 5, the sumfrequency of mixer 501 is removed by low pass filter 503, and the sumfrequency of mixer 502 is removed by low pass filter 504. The mixerfrequency f₀ of mixers 501 and 502 is adjusted and the low pass filters503 and 504 are set to maximize the SNR of the incoming signals S(t).For one embodiment, the mixer frequency f₀ of the mixers 501 and 502 issoftware selectable from a plurality of frequencies. For one embodiment,mixer frequency f₀ of the mixers 501 and 502 is selected from the set ofdiscrete values, e.g., 40 MHz, 80 MHz, 36 MHz, and 30 MHz. For anotherembodiment, frequency f₀ of the mixers 501 and 502 is selectable fromthe frequencies in the approximate range of 1 MHz to 500 MHz using astate of the art digital frequency synthesizer Mixer frequencies may beprovided internally, or externally. The use of external mixer frequencyallows operation of all the mixers for multi-channel applications withthe frequency used for optical shifter drivers, e.g., Bragg celldrivers. This provides more accurate near zero velocity measurements. Asshown in FIG. 5, quadrature signals S_(i)(t) from LPF 503 and in-phasesignals S_(r)(t) from LPF 504 are fed to digital section 303.

Referring back to FIG. 3, quadrature signals S_(i)(t) and in-phasesignals S_(r)(t) from analog section 302 are sampled in digital section303 with a sampling frequency. For one embodiment, a transit time τ,e.g., a minimum transit time, and a mean transit time, of the Dopplerburst signals sets the sampling frequency. Digital section 303 providessampling and digitizing of the analog electrical signals using anadaptive sampling technique, as described below with respect to FIGS. 6,7-11. Digital section 303 also provides assembly of data packets, asdescribed in further detail below with respect to FIG. 6.

Digital section 303 can sample the analog signals with samplers that mayhave either one bit or multibit quantization. For multibit quantizationsignal is digitized with a range of resolution on amplitude. Thesampling frequency of an analog to digital converter of the digitalsection 303 samples the analog signals at a frequency greater than twiceof the signal frequency to satisfy the Nyquist criteria. Nyquistcriteria are known to one of ordinary skill in the art of electronicsdevices manufacturing. To accommodate the wide dynamic range of signalburst transit time, the digital section 303 of the signal processor 300is supported with a wide range of sampling frequencies. The analogsignals from analog section 302 are sampled at a rate that allowsobtaining a sufficient number of samples for accurate frequency andphase measurements. For example, the sufficient number of samples forthe frequency measurements may be such that the frequency measurementaccuracy is within about +/−0.1% margins. For example, the sufficientnumber of samples for the phase measurements may be such that the phasemeasurement accuracy is within about +/−2 degrees. For the optimummeasurement accuracy, sampling is performed over the full signal burst.For one embodiment, to obtain the sufficient number of samples toaccurately determine the frequency and phase of the signals, thesampling frequency of digital section 303 is varied depending on thetransit time (e.g., mean transit time, and minimum transit time) ofsignal bursts. For one embodiment, the sampling frequency of digitalsection 303 is software selectable from a plurality of frequencies. Forone embodiment, the sampling frequency of digital section is obtained bya subsequent division of the master clock frequency of 160 MHz by 2. Forone embodiment, the sampling frequency ranges from about 160 MHz toabout 1.25 MHz. For one embodiment, the digitized, sampled data signalmay be applied to a digital burst detector to determine when a burstsignal is present in the continuously sampled record, as described belowwith respect to FIG. 6. For one embodiment, the signal burst detectoroutput is combined with an analog burst detector output with apre-selected threshold voltage level and then used as an input to theadaptive sampling circuitry, as described below with respect to FIG. 6.With the detection of a Doppler burst signal, a data packet isassembled. That is, the sampled data for each Doppler burst signal ispacked into a single data packet.

Because the transit time for burst signals may vary over a wide dynamicrange (in some cases in excess of 1:100), an adaptive sampling techniqueis employed for sampling the data. The adaptive sampling techniqueprovides a variable number of samples in each data packet that isadaptive to the width (e.g., transit time) of the burst signal. That is,the size of the data packet is variable. To avoid problems withsynchronization errors while handling the data packets with variablesizes, a synchronizing technique may be employed. For example, eachvariable size data packet may have a number of synchronization words.Additionally, each data packet may be stamped with two numbers. Thefirst number may be the total number of words in the data packet. Thesecond number may be a channel (e.g., component) number from which thedata packet is originated. Other parameters that are relevant to thesetting of the signal processor may be measured and assembled into thedata packet. These parameters may include, for example, the peak signalintensity, transit time, time of arrival, elapsed time, and externalinput data.

As shown in FIG. 3, a data packet is transferred from digital section303 computer interface 304, e.g., a high speed I/O card. For example,the data packet may be transferred to a main FIFO on the I/O card.Further, the data packet may be transferred via a PCI interface 316 to amemory 318 of a computer 317 for processing using the complex Fouriertransform to obtain the signal frequency and phase information.

Computer 317 unpacks each data packet to recover the sampled data andthe other relevant information (e.g., time of arrival, transit time,elapsed time, peak signal intensity, and external input data) containedin the data packet. The sampled data is then processed and used tocompute the frequency and the phase. For one embodiment, computer 317processes the sampled data using a Fast Fourier Transform algorithm. Foranother embodiment, computer 317 processes the sampled data using anautocorrelation plus counting approach. To improve the frequency andphase resolution, validation criteria may be used to accept or rejecteach data packet. The validation criteria may include a signal-to-noiseRatio (SNR) of the sampled data that is computed using, e.g., theFourier analysis method. To measure the size of the spherical objects,the SNR for each of the three photodetector channels is computed andused to validate the measurement.

FIG. 6 shows a block diagram of one embodiment of a signal processor 600to determine the size and velocity of spherical objects. As shown inFIG. 6, signal processor 600 includes a photodetector section 601, ananalog section 602, a digital section 603, and a digital/analog burstdetector section 604. As shown in FIG. 6, digital section 603 is coupledto a processing unit 605, e.g., a microcontroller. For one embodiment,processing unit 605 can be a microprocessor, such as an Intel Pentium®microprocessor, Motorola Power PC® microprocessor, Intel Core™ Duoprocessor, AMD Athlon™ processor, AMD Turion™ processor, AMD Sempron™processor, and any other microprocessor. For one embodiment, theprocessing unit of signal processor 600 includes a CPU, amicrocontroller, a digital signal processor, a microprocessor, apersonal computer (“PC”), or any combination thereof.

For one embodiment, processing unit 605 includes a general purposecomputer system based on the PowerPC®, Intel Core™ Duo, AMD Athlon™, AMDTurion™ processor, AMD Sempron™, HP Pavilion™ PC, HP Compaq™ PC, and anyother processor families. As shown in FIG. 6, processing unit 605 iscoupled to digital section 603 by a bus 615. For one embodiment, bus 615can be Peripheral Component Interconnect (“PCI”) bus, PCI-X, PCIExpress, Universal Serial Bus (“USB”), IEEE 1394 bus (e.g., Firewire®,or any other bus known to one of ordinary skill in the art.

Photodetector section 601 converts light scattered from a sphericalobject to electrical signals. The gain of the photodetector section 601is adjustable, as described in further detail below with respect to FIG.12. For one embodiment, photodetector section 601 includes one or morephotomultiplier tubes (PMTs). For another embodiment, photodetectorsection 601 includes one or more photodetectors having a fixed gain,e.g., PIN and APD photodiodes. Output 611 provides signals fromphotodetector section 601 to digital section 603 to measure, e.g.,signal peak intensity. Output 612 provides signals from photodetectorsection 601 to analog section 602.

Analog section 602 has at least one low pass filter and at least onemixer, as described above with respect to FIG. 5. The signal processorfrequency bandwidth is adjusted by changing the frequency of the mixerand selecting the appropriate LPF to optimize the SNR, as described infurther detail below with respect to FIGS. 7-11. The output signals fromanalog section 602 (e.g., in phase and quadrature signals) are fed todigital section 603 and to burst detector section 604, as shown in FIG.6. Signals (e.g., in-phase and quadrature signals) from analog section602 are sampled by quadrature sampler/digitizer 613 in digital section603 at a sampling frequency. For one embodiment, the transit time (e.g.,minimum transit time) of the Doppler burst signals sets the samplingfrequency of the quadrature sampler/digitizer 613. To determine thetransit time, the sampled data is first applied to the burst detector604. With the detection of each burst signal, a data packet is assembledin portion 614. For one embodiment, portion 614 includes FIFO registersto acquire samples. For one embodiment, portion 614 is configured tomeasure transit times of the burst signals, burst signal peakintensities, and arrival times of the burst signals. Because the transittime of the burst signals can vary over a wide dynamic range (e.g., morethan 1:100), an adaptive sampling technique is employed. That is, usingthe adaptive sampling technique a data packet can be generated, so thatthe size of the data packet depends on the transit time of the burstsignal. Other parameters that are relevant to the setting of the signalprocessor can be also measured and assembled into the data packet. Theseparameters include the peak signal intensity, transit time, and time ofarrival.

For one embodiment, digital section 603 performs measurement of theintensity of the raw signal from photodetector section 601. For anembodiment, digital section 603 generates analog and digital controlsignals for analog section 602 and digital section 603. Analog controlsignals may include analog burst detector thresholds provided to burstdetector section 604 and gain controls (e.g., high voltage controls)provided to photodetector section 601. Digital control signals mayinclude signals for selecting a sampling frequency, a mixer frequency,and a LPF.

Burst detector section 604 includes an analog burst detector and adigital burst detector. The digital burst detector of section 604 cansample signals from analog section 602 at another sampling frequency.The Doppler burst signals are detected over a wide range of signalbandwidth, SNR and amplitude. The digital burst detector interrogatesshort sections of the sampled signal to estimate the SNR to determinethe presence of the signal bursts. For one embodiment, the sampled dataare sampled at twice of the signal bandwidth to ensure that consecutivesamples of the noise are statistically independent and to compute anaccurate estimate of the short record SNR. For one embodiment, thesampling frequency of the quadrature sampler/digitizer is determined bythe minimum transit time of the signal bursts. The sampling frequencycan be more than twice of the signal bandwidth. For this reason, toensure reliable operation of the digital burst detector, the sampleddata are decimated before being applied to the digital burst detector.For one embodiment, a decimation factor is defined as the ratio of thesampling frequency of the quadrature sampler/digitizer 613 to thedigital burst detector sampling frequency. For one embodiment, thedecimation factor is determined by dividing the sampling frequency ofthe quadrature sampler/digitizer (determined, e.g., by the minimumtransit time of the signal bursts) divided by twice the signalbandwidth. The analog burst detector may be also used in burst detectorsection 604 in conjunction with the digital burst detector to determinethe beginning and the end of each Doppler burst.

As shown in FIG. 6, processing unit 605 is coupled to photodetectorsection 601, analog section 602, digital section 603, and burst detectorsection 604. As shown in FIG. 6, processing unit 605 is coupled tophotodetector section 601 to adjust gain 606 of photodetector section601 using methods described below with respect to FIG. 12. For oneembodiment, the gain of photodetector section 601 is adjusted bychanging a high voltage of the PMTs. For another embodiment, the gain ofphotodetector section 601 is adjusted by varying the attenuation of oneor more variable optical attenuators placed in front of thephotodetectors having a fixed gain, e.g., PIN and APD photodetectors. Asshown in FIG. 6, processing unit 605 is coupled to analog section toadjust a mixer frequency and select a low pass filter using methodsdescribed below with respect to FIGS. 7-11. As shown in FIG. 6,processing unit 605 is coupled to digital section to determineparameters of the samples of the signals and provide the samplingfrequency 607 using methods described below with respect to FIGS. 7-11.Processing unit 605 is coupled to burst detector section 604 to providea decimation factor using methods described below with respect to FIGS.7-11.

For one embodiment, signal processor 600 moves automatically from onemeasurement location to another, performs automatic set-ups formeasurement functions at each measurement location, and then acquiresdata using methods described below. For one embodiment, signal processor600 is incorporated in a single package. For one embodiment, signalprocessor 600 is a system-on-chip (“SOC”).

FIG. 7 is a flowchart of one embodiment of a method to automatically setup a signal processing system to determine the sizes and velocities ofthe spherical objects. Method begins with operation 701 that involvessetting the signal processing system to a first bandwidth (“BW₁”) and toa first sampling frequency. For one embodiment, the BW₁ is a full (e.g.,maximum) bandwidth of the signal processing system. For one embodiment,a first sampling frequency (f_(samp1)) is the maximum sampling frequencyof the signal processing system. Operation 701 may be performed inresponse to receiving of a user request. Method continues with operation702 that involves receiving first samples of signals at the firstsampling frequency using the first bandwidth. A number of the firstsamples may be, for example, between about 100 samples to about 1000samples. Next, the first parameters of the signals are determined basedon the first samples at operation 703. For one embodiment, the firstparameters, for example, mean and minimum transit time, mean value ofinput frequency measurements, and standard deviation of the inputfrequency measurements are computed based on the first samples. Further,at operation 704 a minimum input frequency and a maximum input frequencyof the signals are calculated based on the mean and standard deviationvalues. For one embodiment, the maximum input frequency is calculated byadding 3 times the standard deviation to the mean value of the inputfrequency measurements. The minimum input frequency is calculated bysubtracting 3 times the standard deviation from the mean value of theinput frequency measurements. Next, operation 705 is performed thatinvolves determining of a second sampling frequency (f_(samp2)) based onthe first parameters. For one embodiment, the second sampling frequencyis determined for a digital section of the signal processing systemillustrated in FIGS. 3 and 6 to sample second samples. The secondsampling frequency is determined such that the signals having theminimum transit time provide a number of samples exceeding apredetermined threshold and the signals having the mean transit timeprovide a number of samples within a range. For example, the secondsampling frequency is selected such to ensure that each of the burstsignals having the minimum transit time can provide more than about 32samples. For example, the second sampling frequency is selected such toensure that each of the burst signals having the mean transit time canprovide from about 128 to about 256 samples. A number of the secondsamples to provide a single measurement point may be, for example,between about 100 samples to about 1,000 samples. The second samples areused to refine the sampling frequency to better define the transit time.Next, at operation 706, a mixer frequency is determined based on thefirst parameters. For one embodiment, the mixer frequency of the one ormore mixers of the analog section of the signal processing system, asdescribed in FIGS. 3 and 6 is set based on the first samples. For oneembodiment, the mixer frequency is set based on the minimum inputfrequency and maximum input frequency. At operation 707 determination ismade if velocity set-up, e.g., a LDV set-up, or sizing setup, e.g., aPDI set-up, is performed. For one embodiment, at operation 708, if thevelocity set up is performed, the mixer frequency is set to the averageof the estimated maximum input frequency f_(max) and minimum inputfrequency f_(min). For one embodiment, the mixer frequency f_(mix1) isset to f_(mix1)=(f_(max)−f_(min))/2. For one embodiment, at operation709, if the sizing set-up is performed, the mixer frequency is set to0.9 times the estimated minimum frequency. For some PDI applications,the computed mixer frequency is less than the signal bandwidth(estimated by subtracting the estimated maximum frequency from theestimated minimum frequency). For these cases, the mixer frequency isset to 1.1 times of the maximum input frequency. Next, a signalbandwidth (BW₂) is determined at operation 710. For one embodiment, theBW₂ is set as follows:

BW ₂=Max [|f _(mix) −f _(min) |,|f _(max) −f _(mix)|]  (5)

Next, at operation 711 a low pass filter is set based on the mixerfrequency. For one embodiment, one or more low pass filters of theanalog section of the signal processing system as described in FIGS. 3and 6 are set based on the mixer frequency. For one embodiment, the lowpass filter cut-off frequency f_(LPF) is set as follows:

f _(LPF)=1.5*(f _(max) −f _(mix))  (6)

For another embodiment, the low pass filter bandwidth Δf_(LPF) is set asfollows:

Δf_(LPF)=1.5*BW ₂  (7)

Next, at operation 712 a decimation factor F_(dec) is set based on thelow pass filter. The decimation factor is used to ensure that thesampled data are sampled at the digital domain burst detector at twiceof the processor bandwidth, as described above with respect to FIGS. 3and 6. For an embodiment, the processor bandwidth is equal to Δf_(LPF).

For one embodiment, the decimation factor is computed as follows:

F _(dec) =f _(samp2)/(2×Δf _(LPF))  (8)

For one embodiment, operations 701-711 are continuously repeated torefine the selection of the signal processor parameters. For oneembodiment, the signal processor parameters are a mixer frequency, a lowpass filter setting, a sampling frequency, or any combination thereof.

For PDI applications, phase measurements may not be accurate when thesignal frequency is close to the mixer frequency. This is especiallytrue for real signals (e.g., if the imaginary part Si(t) is about zero).

FIGS. 8A-8D illustrate an embodiment of signal spectra. FIG. 8Aillustrates a spectrum of a continuous sinusoidal signal with afrequency fr. As shown in 8A, the spectrum has two frequency components(i.e. positive fr and negative −fr components). The spectrum having theGaussian envelope 801 is shown in FIG. 8 b. As shown in FIG. 8B, thewidth 1/τ of Gaussian envelope 801 is determined by a signal transittime τ. A spectrum of a Doppler Gaussian envelope signal is shown inFIG. 8C. As shown in FIG. 8C, fr>>1/τ and signal components 802 and 803do not interact, and the phase of the signal can be measured accuratelyat fr. A spectrum of another Doppler Gaussian envelope signal is shownin FIG. 8D. As shown in FIG. 8D, fr<1/τ and the interaction between thetwo components 803 and 804 may lead to inaccuracy in the phasemeasurement. To avoid the measurement inaccuracies, the mixer frequencyis selected so that the mixer output has at least 2 cycles within theburst signal. This can be achieved by setting the mixer frequency asfollows:

(f _(i) −f _(mix))×τ_(i) >M  (9)

where, f_(mix) is the mixer frequency, f_(i) is the signal frequency ofthe signal i, τ_(i) is the transit time of the burst signal i, and M isthe minimum number of cycles of the signal used for phase measurement.

For one embodiment, the low pass filter with a cut-off frequency f_(LPF)is then selected as follows:

|f _(min) −f _(mix) |<f _(LPF)  (10)

|f _(max) −f _(mix) |<f _(LPF)  (11)

||f _(min) +f _(mix) |>f _(LPF)  (12)

|f _(max) +f _(mix) |>f _(LPF)  (13)

As described above, the sampling frequency is selected to ensure atleast a minimum number of samples for the shortest duration signalbursts. On the other hand to ensure reliable signal detection in thepresence of noise, the sampling frequency should not be larger thantwice the low pass filter f_(LPF). To accommodate for these twoindependent conditions, a decimation feature is used. For an embodiment,the signal sampling frequency is determined by the minimum transit time,as described above. The signal sampling frequency is then decimated by avariable factor (e.g., any number from about 1 to about 8) to insurereliable signal detection.

FIG. 9 shows a flowchart of another embodiment of a method toautomatically set up a signal processing system to determine the sizesand velocities of the spherical objects. Method begins with operation901 that involves setting the signal processing system to a firstbandwidth (“BW₁”) and to a first sampling frequency. For one embodiment,the BW₁ is a full (e.g., maximum) bandwidth of the signal processingsystem. For one embodiment, a first sampling frequency (f_(samp1)) isthe maximum sampling frequency of the signal processing system. Methodcontinues with operation 902 that involves receiving first samples ofsignals at the first sampling frequency using the first bandwidth. Next,the first parameters of the signals are determined based on the firstsamples at operation 903. For one embodiment, the first parameters, forexample, mean and minimum transit time, mean value of input frequencymeasurements, and standard deviation of the input frequency measurementsare computed based on the first samples. Further, at operation 904 aminimum input frequency and a maximum input frequency of the signals arecalculated based on the mean and standard deviation values. For oneembodiment, the maximum input frequency is calculated by adding 3 timesthe standard deviation to the mean value of the input frequencymeasurements. The minimum input frequency is calculated by subtracting 3times the standard deviation from the mean value of the input frequencymeasurements. Next, operation 905 is performed that involves determiningof a second sampling frequency (f_(samp2)) based on the firstparameters. For one embodiment, the second sampling frequency isdetermined for a digital section of the signal processing systemillustrated in FIGS. 3 and 6 to sample second samples. The secondsampling frequency is determined such that the signals having theminimum transit time provide a number of samples exceeding apredetermined threshold and the signals having the mean transit timeprovide a number of samples within a range. For example, the secondsampling frequency is selected such as to ensure that the burst signalshaving the minimum transit time can provide more than about 32 samples.For example, the second sampling frequency is selected such to ensurethat the burst signals having the mean transit time can provide fromabout 128 to about 256 samples. Next, a determination is made atoperation 906 whether the second sampling frequency is an integermultiple of the signal frequency. If the second sampling frequency is aninteger multiple of the signal frequency, at operation 907 a thirdsampling frequency is set that is not an integer multiple of the signalfrequency. If the second sampling frequency is not an integer multipleof the signal frequency, the method 900 continues with operation 908.Operation 908 involves setting a mixer frequency based on the firstparameters, as described above with respect to FIG. 7. Method 900continues with operation 909 that involves setting a low pass filterbased on the mixer frequency, as described above with respect to FIG. 7.Next, at operation 910 a decimation factor is determined based on theLPF setting, as described above with respect to FIG. 7.

For an embodiment, method 900 is used to resolve ambiguity in phasemeasurements that occurs when the sampling frequency is an integermultiple of the signal frequency.

FIG. 10 illustrates one embodiment of complex signal data in the absenceof noise when the sampling frequency is four times the input signal. Asshown in FIG. 10, sampled data 1001-1004 repeats itself after the fourthsample and the phase measurement accuracy may not improve by increasingthe number of samples over 4. For this case, the phase measurementaccuracy may be determined by the digitization noise. For N-bitAnalog-to-Digital converter (“ADC”), the phase measurement ambiguity Δθcan be determined as follows:

Δθ=sin⁻¹(1/2^(N))  (14)

For PDI applications.

Using the adaptive sampling techniques where the signal is sampled atdifferent rates overcomes the ambiguity in phase measurements andprovides a phase measurement accuracy at least better than 2 degrees.The sampling frequencies are selected such that if one of the samplingfrequencies is a multiple integer of the signal frequency, anothersampling frequency that is not a multiple integer of the signalfrequency is selected. For one embodiment, the frequency of the incomingsignals can be measured using any of these sampling frequencies, and thephase of the incoming signals is measured using only the data sampled ata rate that is not a multiple integer of the signal frequency.

FIG. 11 shows the signal sampled data using two sampling frequenciesaccording to one embodiment of the invention. The sampled data A areobtained with the first sampling frequency that is four times the signalfrequency. The sampled data B are obtained with a second frequency thatis higher than the first sampling frequency. As shown in FIG. 11, whensamples A do not effectively span complex plain 1101, samples Beffectively span complex plain 1101.

FIG. 12 is a flowchart of another embodiment of a method toautomatically set up a signal processing system to determine the sizesand velocities of the spherical objects that includes automaticallyadjusting a gain. An analog front-end gain of the photodetector sectionof the signal processing system may vary over the range of 100 to morethan 10000 depending on the strength of the optical signals. The gain ofthe signal processing system can be adjusted to accommodate a wide rangeof the amplitudes of the incoming signals. The amplitude range of theincoming signals may vary, for example, over the range of 1:10000.Method 1200 begins with operation 1201 that involves setting a gain ofthe signal processing system to a first value e.g., an intermediatevalue. For one embodiment, the gain of the signal processing system isan analog front-end gain of the photodetector section of the signalprocessing system described above with respect to FIGS. 3 and 6. Method1200 continues with operation 1202 that involves measuring intensitiesof the first samples. For one embodiment, the intensities (oramplitudes) of the incoming optical signals from a spherical object aremeasured. For one embodiment, the first samples to measure theintensities are sampled with a first sampling frequency, e.g., a maximumsampling frequency and at a full bandwidth of the signal processingsystem, or any other sampling frequency. Next, at operation 1203, thegain is automatically adjusted to a second value based on the measuredintensities (or amplitudes), so that a smallest intensity of theincoming signals is higher or equal to a minimum detection level of thesystem and a largest intensity of the incoming signals is less or equalto a saturation level of the system. For one embodiment, a histogram isgenerated based on the measured intensity or amplitude of the incomingoptical signals. The histogram is then used to determine the optimumsystem front-end gain. For one embodiment, the gain is adjusted byadjusting the High Voltage (HV) of the photodetectors (e.g., PMTs) usedin the photodetector section of the signal processing system. For oneembodiment, HV is adjusted automatically by using the gain-HVdependencies supplied by a photodetector manufacture, to ensure that allthe signals fall between the system minimum detection level and thesaturation level. For another embodiment, the gain is adjusted to thesecond value by attenuating optical signals in front of a photodetector,using, for example, a variable optical attenuator.

For another embodiment, dependencies of the sampled signal amplitudefrom the measured drop size may be used to adjust the gain of the signalprocessing system.

For one embodiment, the amplitude of the signal for a selected number ofsignals is measured and compared to the optimum signal amplitude. Thespherical objects typically scatter light in proportion to theirdiameter squared. For example, for a size range from about 50 to about1, the signal amplitude range may vary from about 2500 to about 1. Inorder to be able to detect and measure the smallest particles withoutexceeding the amplitude limits for the large particles, the gain of thephotodetectors (e.g., PMTs) is adjusted. Because the size range of thespherical objects may vary from point-to-point within the spray orparticle field, the adjustment of the gain is performed rapidly andrepeatedly to provide an appropriate photodetector gain setting for eachmeasurement location. For one embodiment, the gain of the photodetectorsis adjusted to fit peak amplitudes of the incoming signals to aparabolic theoretical signal amplitude curve for each particle sizeclass. Each of the particle size class has a range of signal amplitudes.For an embodiment, an automatic photodetector gain adjustment at eachmeasurement location serves to accommodate any laser beam attenuation,scattered light attenuation, change in the drop size distribution, andwindow contamination.

The automatic gain adjustment allows automatic traversing of the spraypattern without user intervention. At each measurement location, thegain is automatically adjusted to measure the spray or particle fieldhaving different characteristics. By automating the signal processingsystem setup, the entire traversing and data acquisition process can befully automated so that system can perform multitude of measurementswithout the need for an instrument user to be present to make thechanges and adjustments at each measurement location.

FIG. 13 is a flowchart of one embodiment of a method to automaticallyset up a signal processing system to determine the sizes and velocitiesof the spherical objects that includes automatically adjusting anaperture of the signal processing system. The aperture of the signalprocessing system is adjusted to accommodate current density of thespherical objects. Method begins with operation 1301 that involvesmeasuring parameters of spherical objects passing through a first samplevolume. For one embodiment, the parameters of the spherical objectsinclude the arrival rate of the spherical objects passing through thesample volume. For one embodiment, a mean arrival rate of the sphericalobjects passing through the sample volume is measured. For oneembodiment, the arrival rate can be calculated based on the time ofarrival of the spherical object to the sample volume. For anotherembodiment, the parameters of the spherical objects include the distancebetween the spherical objects passing through the sample volume. For oneembodiment, the distance between the spherical objects passing throughthe sample volume includes an inter-arrival time between the sphericalobjects. For another embodiment, a mean distance between the sphericalobjects passing through the sample volume is measured. For anotherembodiment, the distance between the spherical object passing throughthe sample volume is calculated based on the velocity of the sphericalobjects and arrival time of the spherical objects.

Method continues with operation 1302 that involves determining aprobability that more than one spherical object resides at a time in thefirst sample volume is less than a predetermined threshold based on themeasured parameters. For one embodiment, the predetermined threshold isdefined as is a preset percentage, e.g., about 20%. For one embodiment,the probability that more than one spherical object resides at a time inthe first sample volume is determined by applying probability analysis,e.g., a Poisson statistics. The probability analysis is applied toselect the optimum sample volume size to limit coincidence error andmaximize data rates. For one embodiment, an alert signal isautomatically issued when an optics of the signal processing systemneeds to be changed. Next, the operation 1303 is performed that involvesautomatically adjusting the aperture of the signal processing systembased on the probability to provide a second sample volume. For oneembodiment, the aperture of the signal processing system includes amovable strip-like slit aperture positioned in front of thephotodetector section of the signal processing system, as describedabove with respect to FIG. 2. For an embodiment, an adjustable aperturehaving a round or rectangular shape, or any other aperture that is knownto one of ordinary skill in the art of optics manufacturing is used.

Typically, single particle counter-based measurements to determine thesizes and velocities of the spherical objects require a substantiallyhigh probability, for example more than about 90% that only one particleexists in the measurement volume (sample volume) at one time. Thisrequirement may be analyzed using a probability analysis, e.g., Poissonstatistics. Larger the density of the spherical objects, smaller samplevolume is required to ensure that this condition is met. For example, indense sprays, a substantially small volume is required. When the densityof the spray or particle field is low, a larger sample volume may berequired to maintain an adequate data rate. For one embodiment, insprays where the number density of the spray is very low at the edgesand increases to a relatively high number density at the center of thespray, the sample volume is adjusted as described above to accommodateeach location to optimize the data acquisition. As such, an automaticselection and recording of the aperture limits coincidence errors. Theprobability analysis approach assures that a statistically significantnumber of samples, e.g., at least 1000 samples, are acquired for eachlocation in the spray field. By adjusting the sample volume size foreach measurement location based on the probability analysis, thesubstantially high data acquisition rate is maintained while the loss ofdata due to coincidence errors is minimized. A coincidence error mayoccur when more than one spherical object occupies the sample volume.Further, using the probability analysis to adjust the sample volumeensures that data are not lost because of signal rejections when morethan one spherical object occupies the sample volume.

FIG. 14 is a flowchart of one embodiment of a method to automaticallyset up a signal processing system to determine the sizes and velocitiesof the spherical objects that includes automatically estimating ameasurement uncertainty of the signal processing system for each of themeasured spherical objects. Method 1400 begins with operation 1401 thatinvolves receiving samples of signals from a signal source. Methodcontinues with operation 1402 of measuring first parameters of thesamples on photodetectors. The first parameters include measuring asignal-to-noise ratio of the samples of each of the signals on each ofthe photodetectors. Next, estimating a first relative number of thesamples that pass one or more first parameter validation criteria areperformed at operation 1403. For example, the relative number of thesamples that have S/N ratios that exceed a predetermined threshold >50%,are estimated. The S/N ratio for each of the photodetector outputs iscomputed by computing the power spectrum of the signal using theDiscreet Fourier Transform (“DFT”). The signal power is then computed bycomputing the power of the DFT bin (bins) with maximum power. The S/Nratio is then computed by dividing the signal power by the sum of thepower of the remaining DFT bins. The S/N ratio can be set to any valuebetween 0 dB to 10 dB depending on the level of measurement uncertainty.For one embodiment, the relative number of the samples that pass one ormore first parameter validation criteria are estimated using statisticalmethods. Method continues with operation 1404 that includes determininga first measurement uncertainty based on the estimated first relativenumber of the samples. For one embodiment, the first measurementuncertainty is estimated quantitatively based on the first number. Next,second parameters of the samples of the signals are measured atoperation 1405. For one embodiment, the second parameters include phasedifferences of the samples of the signals between each of thephotodetectors. For one embodiment, the second parameters includecomparison of measurements of the phase difference between photodetectorsignals using different sections of the signals. For example, thephotodetector signals are divided into a first half and a second half.The phase difference is then measured for the first half and the secondhalf. These two measurements should agree within a few degrees, e.g.,within about 10 degrees. For one embodiment, the phase comparison foreach of the three pairs of detectors is performed. For one embodiment,each of the signals is evaluated in sections over the duration of thesignal to determine the phase. For another embodiment, the secondparameters include frequencies of the samples of the incoming signals.For one embodiment, the signal is divided into several sections (e.g., afirst half and a second half). The frequencies of these sections shouldagree within a few KHz, e.g., about 10 KHz. At operation 1406 estimatinga second relative number of the samples that pass one or more secondparameter validation criteria is performed. For example, the relativenumber of the samples that have the second parameters (e.g., phasedifferences, frequency differences, or a combination thereof) thatexceed a predetermined threshold >50%, are estimated. For oneembodiment, the relative number of the samples that pass one or moresecond parameter validation criteria are estimated using statisticalmethods.

Next, a second measurement uncertainty is determined based on the secondnumber at operation 1407. For one embodiment, the second measurementuncertainty is estimated quantitatively based on the first number.Further, method 1400 continues with operation 1408 that includesdetermining a global measurement uncertainty. For one embodiment, theglobal measurement uncertainty is determined based on the firstmeasurement uncertainty and the second measurement uncertainty. For oneembodiment, each of a first measurement uncertainty and the secondmeasurement uncertainty is determined after measuring both the firstparameters and second parameters. For another embodiment, the globalmeasurement uncertainty is determined based on the first relative numberand the second relative number. For one embodiment, a plurality ofparameter measurement uncertainties is quantitatively estimated for eachof the parameters of the signals, and then the global measurementuncertainty is quantitatively estimated based on each of the parametermeasurement uncertainties. Next, method 1400 continues with operation1409 that includes determining a distribution of parameters of thespherical objects using the global measurement uncertainty. Theuncertainty for each of the measured spherical object can beincorporated into the calculation of the mean values for the measuredsize and velocity distributions. For one embodiment, the measurementdata are acquired until a user-defined uncertainty band has beenreached. For one embodiment, the parameters of the spherical objectsinclude sizes of the spherical objects, velocities of the sphericalobjects, or a combination thereof. For one embodiment, the validationinformation (e.g., validation criteria) are stored in a memory of theprocessing system with each data set. For one embodiment, validationcriteria are developed to estimate the measurement uncertainty at eachmeasurement location.

FIG. 15 is a flowchart of one embodiment of a method to automaticallyset up a signal processing system to determine the sizes and velocitiesof the spherical objects that includes an automated detectorcalibration. Method begins with operation 1501 that involves receivingfirst signals to characterize the components of the signal processingsystem. For one embodiment, the first signals to characterize thecomponents are sent to the signal processing system from a calibrationsource, e.g., a built-in laser diode. The components of the signalprocessing system are for example, cables, photodetectors,pre-amplifiers, amplifiers, and filters, and any other active andpassive components that may have varying time response. Method continueswith operation 1502 that involves measuring first parameters of thefirst signals to characterize the components of the system at anoperating condition. For one embodiment, the first parameters of thefirst signals to characterize the components of the system are measuredautomatically in response to changing of the operating condition. Forone embodiment, the first parameters are, for example, time responses,time delays, and phase shifts that characterize the components. For oneembodiment, the operating condition of the signal processing system is again setting, an operating frequency, a filter setting, other systemsetting, or any combination thereof. For one embodiment, the measuringof the first parameters includes setting a shutter coupled to thephotodetector section of the system “ON” to avoid scattered light. Forone embodiment, a look up table based on the measurements from thecalibration diode is automatically generated based on the measured firstparameters. The look up table includes measured first parameters (e.g.,time responses, time delays, and phase shifts) at each of a plurality ofoperating conditions. For one embodiment, the look up table isautomatically generated periodically to follow a current operating(measurement) condition. For one embodiment, the look-up table isautomatically generated at each new operating condition. For oneembodiment, the look-up table is automatically generated when one ormore operating conditions change. For one embodiment, the look up tablethat includes measured first parameters at each of the plurality ofoperating conditions is stored in a memory of the system to measure thesize and velocity of spherical objects.

Next, at operation 1503 second signals are received. For one embodiment,second signals are received from a spherical object passing through asample volume. Next, operation 1504 is performed that involves measuringsecond parameters of the second signals to characterize sphericalobjects. For one embodiment, the second parameters to characterize thespherical objects are e.g., phases, frequencies, and amplitudes of thesecond signals. For one embodiment, the measuring of the secondparameters includes setting a shutter coupled to the photodetectorsection of the system “OFF” to receive the optical signals from thespherical objects. Further, operation 1505 is performed that involvesautomatically adjusting the second parameters based on the firstparameters. For one embodiment, the second parameters are adjusted bysubtracting the first parameters from the second parameters. For oneembodiment, the second parameters are automatically adjusted based onthe look-up table stored in the memory. That is, the second parameterscan be automatically adjusted when one or more operating conditionschange. For another embodiment, moving to another measurement locationis performed, and operations 1501-1505 are repeated at anothermeasurement location to calibrate the system. As such, method 1500 isused to calibrate the signal processing system at each location tomeasure the size and velocity of the spherical objects. Method 1500accounts for all possible phase delays in the components of the systembefore measuring the size and velocity of the spherical particles. Thesystem to measure the size and velocity of the spherical objects iscalibrated using the method 1500 at the full range of frequencies forset up. For one embodiment, the system automatically steps through theoperating frequencies at the set-up conditions and tabulates the phaseshifts. For one embodiment, first signals and the second signals are inthe approximate range of 20 MHz to 100 MHz. For one embodiment, timedelays of the signals are in the approximate range of 0.1-100 nsec.Method 1500 performs calibration automatically and covers parameters ofall components of the system. This calibration procedure is fullyautomated and invisible to the system user that simplifies the operationof the system and ensures reliable measurements.

In practice, methods described with respect to FIGS. 7, 9, and 12-15 mayconstitute one or more programs made up of machine-executableinstructions. Describing the methods with reference to the flowcharts inFIGS. 7, 9, and 12-15 enables one skilled in the art to develop suchprograms, including such instructions to carry out the operations (acts)represented by logical blocks of the flowcharts depicted in FIGS. 7, 9,and 12-15 on suitably configured machines (the processor of the machineexecuting the instructions from machine-readable media). Themachine-executable instructions may be written in a computer programminglanguage or may be embodied in firmware logic or in hardware circuitry.If written in a programming language conforming to a recognizedstandard, such instructions can be executed on a variety of hardwareplatforms and for interface to a variety of operating systems. Inaddition, the present invention is not described with reference to anyparticular programming language. It will be appreciated that a varietyof programming languages may be used to implement the teachings of theinvention as described herein. Furthermore, it is common in the art tospeak of software, in one form or another (e.g., program, procedure,process, application, module, logic, etc.), as taking an action orcausing a result. Such expressions are merely a shorthand way of sayingthat execution of the software by a machine causes the processor of themachine to perform an action or produce a result. It will be furtherappreciated that more or fewer processes may be incorporated into themethods illustrated in FIGS. 7, 9, 12-15 without departing from thescope of the invention and that no particular order is implied by thearrangement of blocks shown and described with respect to each of FIGS.7, 9, 12-15.

FIG. 16 shows one embodiment of a data and signal processing system todetermine the size and velocity of the spherical objects that isautomatically set up using methods described above. As shown on FIG. 16,system 1600 includes a transmitter 1601 to generate coherent laser beamscrossed at an angle to form a sample volume to illuminate sphericalparticles 1608, as described above with respect to FIGS. 1 and 2. Asshown in FIG. 16, system 1600 includes signal processor 600 that iscoupled to receive the light scattered from the spherical objects 1608,as described above. Signal processor 600 includes a processing unit (notshown). For one embodiment, processing unit 605 can be a microprocessor,such as an Intel Pentium® microprocessor, Motorola Power PC®microprocessor, Intel Core™ Duo processor, AMD Athlon™ processor, AMDTurion™ processor, AMD Sempron™ processor, and any other microprocessor.For one embodiment, the processing unit of signal processor 600 includesa CPU, a microcontroller, a digital signal processor, a microprocessor,a general purpose computer, or any combination thereof. System 1600 caninterface to external systems through a modem or network interface (notshown). It will be appreciated that the modem or network interface canbe considered to be part of the system 1600. This interface can be ananalog modem, ISDN modem, cable modem, token ring interface, satellitetransmission interface, or other interfaces for coupling a computersystem to other computer systems. As shown in FIG. 16, system 1600further includes a memory 1603 coupled to the signal processor 600 by abus 1605. Memory 1603 can be dynamic random access memory (“DRAM”), andcan also include static RAM (“SRAM”). Bus 1605 couples signal processor600 to memory 1603, to non-volatile storage 1604, to subsystem 1607,that can include GPU coupled by a display controller (not shown) to adisplay device (not shown), and to one or more subsystems 1606 that caninclude one or more I/O controllers (not shown) coupled to one or moreI/O devices (not shown). The display controller controls in theconventional manner the display device which can be a cathode ray tube(“CRT”) or liquid crystal display (“LCD”). The input/output devices caninclude a keyboard, disk drives, printers, a scanner, a digital camera,microphones, speakers, network or telephone communication interfaces,and other input and output devices including a mouse or other pointingdevice. The display controller and the I/O controller can be implementedwith conventional well known technology. Non-volatile storage 1604 isoften a magnetic hard disk, an optical disk, a diskette, CD-ROM,magnetic tape, DVD, ROM, Flash memory, or another form of storage oflarge amounts of data. Some of this data is often written, by a directmemory access process, into memory 1603 during execution of software insystem 1600. One of skill in the art will immediately recognize that theterms “computer-readable medium” and “machine-readable medium” includeany type of storage device that is accessible by the signal processor600 and also encompass a carrier wave that encodes a data signal.

It will be appreciated that the data processing system 1600 is oneexample of many possible data processing systems which have differentarchitectures. For example, personal computers based on an Intelmicroprocessor often have multiple buses, one of which can be aninput/output (I/O) bus for the peripherals and one that directlyconnects the processing unit of signal processor 600 and the memory 1603(often referred to as a memory bus). The buses can be connected togetherthrough bridge components that perform any necessary translation due todiffering bus protocols. Bus 1605 can be Peripheral ComponentInterconnect (“PCI”) bus, PCI-X, PCI Express, Universal Serial Bus(“USB”), IEEE 1394 bus (e.g., Firewire®), or any other bus known to oneof ordinary skill in the art.

For one embodiment, signal processor 600 includes a photodetectorsection, an analog section, a digital section, and a digital/analogburst detector section, as described above with respect to FIGS. 3A, 4,5, and 6. For one embodiment, signal processor 600 is incorporated in asingle package. Signal processor 600 is configured to perform automatedset-up methods as described above with respect to FIGS. 1-16. As shownin FIG. 16, memory 1603 and 1604 can store instructions and data for useby signal processor 600. For one embodiment, methods described abovewith respect to FIGS. 7, 9, 12-15 are implemented as a series ofsoftware routines run by system 1600. These software routines compriseinstructions to be executed by processing unit of signal processor 600in the system 1600. These instructions can be stored initially in memory1604. It is to be appreciated that the series of instructions need notto be stored locally, and could be received from a remote storagedevice, such as a server on a network, via a network/communicationinterface. The instructions can be copied from memory 1604 to memory1603 and then accessed and executed by the processing unit of the signalprocessor 600. Memory 1603 and memory 1604 may be used to, storevoltage-gain dependencies for photodetectors, attenuator settings,validation criteria for the measurement uncertainty, saturation anddetection limits for gain settings, sample thresholds and ranges,probability thresholds, look-up tables for calibration, measured andprocessing data, as described above. Subsystem 1606 can include known inthe art audio processing hardware and/or software to transform analogvoice data to a digital form. For one embodiment, system 1600 movesautomatically from one measurement location to another, performsautomatic set-ups for measurement functions at each measurementlocation, and then acquires data using methods described above. For oneembodiment, system 1600 is incorporated in a single package. For oneembodiment, system 1600 is a system-on-chip (“SOC”).

The above description of FIG. 16 is intended to provide an overview ofthe data processing system hardware and other operating componentssuitable for performing the methods of the invention described above,but is not intended to limit the applicable environments. Embodiments ofthe invention can be practiced with other computer systemconfigurations, including hand-held devices, multiprocessor systems,microprocessor-based or programmable consumer electronics, network PCs,minicomputers, mainframe computers, and the like. The embodiments of theinvention can also be practiced in distributed computing environmentswhere tasks are performed by remote processing devices that are linkedthrough a communications network, such as peer-to-peer networkinfrastructure.

Data processing system 1600 can be controlled by operating systemsoftware which includes a file management system, such as a diskoperating system, which is part of the operating system software. Oneexample of an operating system software with its associated filemanagement system software is the family of operating systems known asWindows® from Microsoft Corporation of Redmond, Wash., and theirassociated file management systems. The file management system can bestored in non-volatile storage 1604 and can cause the processor unit ofsignal processor 600 to execute the various acts required by theoperating system to input and output data and to store data in memory,including storing files on non-volatile storage 1604.

In the foregoing specification, embodiments of the invention have beendescribed with reference to specific exemplary embodiments thereof. Itwill be evident that various modifications may be made thereto withoutdeparting from the broader spirit and scope of the invention. Thespecification and drawings are, accordingly, to be regarded in anillustrative sense rather than a restrictive sense.

1. A machine-implemented method to automatically set-up a instrument formeasuring spherical objects, comprising: setting the system to a firstbandwidth; setting a sampling frequency to a first sampling frequency;receiving first samples of first signals at the first bandwidth and thefirst sampling frequency; determining first parameters of the firstsignals based on the first samples; determining a second samplingfrequency based on the first parameters to sample second samples.
 2. Themachine-implemented method of claim 1, wherein the first parametersinclude a mean transit time, a minimum transit time, a mean frequency ofthe signals, and a standard deviation of the frequency of the signals.3. The machine-implemented method of claim 1, further comprisingdetermining a mixer frequency based on the first parameters.
 4. Themachine-implemented method of claim 3, further comprising setting a lowpass filter based on the mixer frequency; and setting a decimationfactor based on the low pass filter.
 5. The machine-implemented methodof claim 1, further comprising setting a gain to a first value;measuring intensities of the first samples; and adjusting the gain to asecond value based on the intensities, so that a smallest intensity ofthe signals is higher or equal to a detection level of the system and alargest intensity of the signals is less or equal to a saturation levelof the system.
 6. The machine-implemented method of claim 1, furthercomprising setting a third sampling frequency to sample the secondsamples, if the second sampling frequency is an integer multiple of thefrequency of the signals.
 7. The machine-implemented method of claim 1,further comprising determining second parameters of the sphericalobjects passing through a first sample volume; determining a probabilitythat more than one spherical object resides at a time in the firstsample volume is less than a predetermined threshold based on the secondparameters; and adjusting an aperture based on the probability.
 8. Themachine-implemented method of claim 7, wherein the second parameters aredistances between the spherical objects.
 9. The machine-implementedmethod of claim 7, wherein the second parameters are arrival rates ofthe spherical objects to the first sample volume.
 10. Themachine-implemented method of claim 1, further comprising measuringthird parameters of the first samples; estimating a relative number ofthe first samples that pass a validation criterion for each of the thirdparameters; determining a measurement uncertainty based on theestimating.
 11. The machine-implemented method of claim 8, wherein thethird parameters are signal-to-noise ratios of the signals onphotodetectors, phase differences of the signals using differentsections of the signals on the photodetectors, frequencies of thesignals using different sections of the signals on the photodetectors,or any combination thereof.
 12. The machine-implemented method of claim1, further comprising receiving second signals; measuring fourthparameters of the second signals to characterize components of thesystem; measuring fifth parameters of the first signals to characterizethe spherical objects; and adjusting fifth parameters based on thefourth parameters.
 13. The machine-implemented method of claim 12,wherein the fourth parameters include time responses of the components.14. The machine-implemented method of claim 12, wherein the fifthparameters include a phase of the signals.
 15. The machine-implementedmethod of claim 12, wherein the fifth parameters include the frequencyof the signals.
 16. A machine-implemented method to adjust a gain of asignal processing system, comprising: setting a gain to a first value;receiving signals; measuring intensities of the signals; and adjustingthe gain to a second value based on the intensities, so that a smallestintensity of the signals is higher or equal to a detection level of thesystem and a largest intensity of the signals is less or equal to asaturation level of the system.
 17. The machine-implemented method ofclaim 16, further comprising generating a histogram based on theintensities.
 18. The machine-implemented method of claim 16, wherein theadjusting the gain includes adjusting a high voltage of aphotomultiplier tube.
 19. The machine-implemented method of claim 16,wherein the adjusting the gain to the second value includes attenuatingoptical signals in front of a photodetector.
 20. A machine-implementedmethod to adjust an aperture, comprising: measuring parameters ofspherical objects passing through a first sample volume; determining aprobability that more than one spherical object resides at a time in thefirst sample volume is less than a predetermined threshold based on theparameters; and adjusting the aperture based on the probability.
 21. Themachine-implemented method of claim 20, wherein the determining theprobability includes applying a Poisson statistics.
 22. Themachine-implemented method of claim 20, wherein the measuring theparameters includes measuring a distance between the spherical objects.23. The machine-implemented method of claim 20, wherein the measuringthe parameters includes measuring an arrival rate of the sphericalobjects.
 24. A machine-implemented method to estimate a measurementuncertainty of a signal processing system, comprising: receiving samplesof signals; measuring first parameters of the samples on photodetectors;estimating a first number of the samples that pass a first parametervalidation criterion; measuring second parameters of the samples of thesignals; estimating a second number of the samples that pass a secondparameter validation criterion; and determining a global measurementuncertainty based on the first number and the second number.
 25. Themachine-implemented method of claim 24, wherein the first parametersinclude signal-to-noise ratios.
 26. The machine-implemented method ofclaim 24, wherein the second parameters include phases.
 27. Themachine-implemented method of claim 24, wherein the second parametersinclude frequencies.
 28. The machine-implemented method of claim 24,further comprising determining a distribution of third parameters of thespherical objects using the global measurement uncertainty.
 29. Amachine-implemented method to calibrate a signal processing system,comprising: a) receiving first signals; b) measuring first parameters ofthe first signals to characterize components of the system at anoperating condition; c) receiving second signals; d) measuring secondparameters of the second signals to characterize spherical objects; ande) adjusting the second parameters based on the first parameters. 30.The machine-implemented method of claim 29, further comprisinggenerating a look up table based on the measuring the first parametersat each of a plurality of operating conditions.
 31. Themachine-implemented method of claim 29, further comprising moving toanother location; and repeating operations a-e.
 32. Themachine-implemented method of claim 29, wherein the first parametersinclude time responses of the components.
 33. The machine-implementedmethod of claim 29, wherein the second parameters include phases of thesecond signals from the spherical objects.
 34. The machine-implementedmethod of claim 29, wherein the second parameters include frequencies ofthe second signals from the spherical objects.
 35. Themachine-implemented method of claim 29, wherein the operating conditionis a detector gain, a filter setting, a mixer setting, an operatingfrequency, or any combination thereof.
 36. An apparatus, comprising: aphotodetector section to convert a light scattered from a sphericalobject to electrical signals; an analog section coupled to thephotodetector section, wherein the analog section has a low pass filterand a mixer; a digital section coupled to the analog section to samplethe electrical signals; and a processor coupled to the photodetectorsection, the analog section, and the digital section, wherein the signalprocessor is configured to receive first samples of first electricalsignals at a first bandwidth and a first sampling frequency of thedigital section; to determine first parameters of the first signalsbased on the first samples; and to determine a second sampling frequencyfor the digital section based on the first parameters to sample secondsamples.
 37. The apparatus of claim 36, wherein the first parametersinclude a mean transit time, a minimum transit time, a mean frequency ofthe signals, and a standard deviation of the frequency of the signals.38. The apparatus of claim 36, wherein the processor is furtherconfigured to determine a mixer frequency based on the first parameters.39. The apparatus of claim 36, wherein the processor is furtherconfigured to set the low pass filter based on the mixer frequency. 40.The apparatus of claim 36, wherein the processor is further configuredto set a gain of the photodetector section.
 41. The apparatus of claim36, wherein the processor is further configured to set a third samplingfrequency to sample the second samples, if the second sampling frequencyis an integer multiple of the frequency of the signals.
 42. Theapparatus of claim 36, further comprising an adjustable aperture coupledto the photodetector section.
 43. The apparatus of claim 36, wherein theprocessor is further configured to determine a measurement uncertainty.44. The apparatus of claim 36, wherein the processor is furtherconfigured to automatically calibrate at least the photodetectorsection.
 45. A system, comprising: means for setting the system to afirst bandwidth; means for setting a sampling frequency to a firstsampling frequency; means for receiving first samples of first signalsat the first bandwidth and the first sampling frequency; means fordetermining first parameters of the first signals based on the firstsamples; and means for determining a second sampling frequency based onthe first parameters to sample second samples.
 46. A system, comprising:means for setting a gain to a first value; means for receiving signals;means for measuring intensities of the signals; and means for adjustingthe gain to a second value based on the intensities, so that a smallestintensity of the signals is higher or equal to a detection level of thesystem and a largest intensity of the signals is less or equal to asaturation level of the system.
 47. A system, comprising: means formeasuring parameters of spherical objects passing through a first samplevolume; means for determining a probability that more than one sphericalobject resides at a time in the first sample volume is less than apredetermined threshold based on the parameters; and means for adjustingthe aperture based on the probability.
 48. A system, comprising: meansfor receiving samples of signals; means for measuring first parametersof the samples on photodetectors; means for estimating a first number ofthe samples that pass a first parameter validation criterion; means formeasuring second parameters of the samples of the signals; means forestimating a second number of the samples that pass a second parametervalidation criterion; and means for determining a global measurementuncertainty based on the first number and the second number.
 49. Asystem, comprising: means for receiving first signals; means formeasuring first parameters of the first signals to characterizecomponents of the system at an operating condition; means for receivingsecond signals; means for measuring second parameters of the secondsignals to characterize spherical objects; and means for adjusting thesecond parameters based on the first parameters.
 50. An article ofmanufacture, comprising: a machine-accessible medium including datathat, when accessed by a machine, cause the machine to performoperations comprising, setting the system to a first bandwidth; settinga sampling frequency to a first sampling frequency; receiving firstsamples of first signals at the first bandwidth and the first samplingfrequency; determining first parameters of the first signals based onthe first samples; and determining a second sampling frequency based onthe first parameters to sample second samples.
 51. The article ofmanufacture of claim 50, wherein the first parameters include a meantransit time, a minimum transit time, a mean frequency of the signals,and a standard deviation of the frequency of the signals.
 52. Thearticle of manufacture of claim 50, wherein the machine-accessiblemedium further includes data that cause the machine to performoperations, comprising determining a mixer frequency based on the firstparameters.
 53. The article of manufacture of claim 52, wherein themachine-accessible medium further includes data that cause the machineto perform operations, comprising setting a low pass filter based on themixer frequency.
 54. The article of manufacture of claim 50, wherein themachine-accessible medium further includes data that cause the machineto perform operations, comprising setting a gain to a first value;measuring intensities of the first samples; and adjusting the gain to asecond value based on the intensities, so that a smallest intensity ofthe signals is higher or equal to a detection level of the system and alargest intensity of the signals is less or equal to a saturation levelof the system.
 55. The article of manufacture of claim 50, wherein themachine-accessible medium further includes data that cause the machineto perform operations, comprising setting a third sampling frequency tosample the second samples, if the second sampling frequency is aninteger multiple of the frequency of the signals.
 56. The article ofmanufacture of claim 50, wherein the machine-accessible medium furtherincludes data that cause the machine to perform operations, comprisingdetermining second parameters of spherical objects passing through afirst sample volume; determining a probability that more than onespherical object resides at a time in the first sample volume is lessthan a predetermined threshold based on the second parameters; andadjusting an aperture based on the probability.
 57. The article ofmanufacture of claim 56, wherein the second parameters are distancesbetween the spherical objects.
 58. The article of manufacture of claim56, wherein the second parameters are arrival rates of the sphericalobjects to the first sample volume.
 59. The article of manufacture ofclaim 50, wherein the machine-accessible medium further includes datathat cause the machine to perform operations, comprising measuring thirdparameters of the first samples; estimating a relative number of thefirst samples that pass a validation criterion for each of the thirdparameters; and determining a measurement uncertainty based on theestimating.
 60. The article of manufacture of claim 59, wherein thethird parameters are signal-to-noise ratios of the signals onphotodetectors, phase differences of the signals using differentsections of the signals on the photodetectors, frequencies of thesignals using different sections of the signals on the photodetectors,or any combination thereof.
 61. The article of manufacture of claim 50,wherein the machine-accessible medium further includes data that causethe machine to perform operations, comprising receiving second signals;measuring fourth parameters of the second signals to characterizecomponents of the system; measuring fifth parameters of the firstsignals to characterize spherical objects; and adjusting fifthparameters based on the fourth parameters.
 62. The article ofmanufacture of claim 61, wherein the fourth parameters include timeresponses of the components.
 63. The article of manufacture of claim 61,wherein the fifth parameters include a phase of the signals.
 64. Thearticle of manufacture of claim 61, wherein the fifth parameters includethe frequency of the signals.
 65. An article of manufacture, comprising:a machine-accessible medium including data that, when accessed by amachine, cause the machine to perform operations comprising, setting again to a first value; receiving signals; measuring intensities of thesignals; and adjusting the gain to a second value based on theintensities, so that a smallest intensity of the signals is higher orequal to a detection level of the system and a largest intensity of thesignals is less or equal to a saturation level of the system.
 66. Thearticle of manufacture of claim 65, wherein the machine-accessiblemedium further includes data that cause the machine to performoperations, comprising generating a histogram based on the intensities.67. The article of manufacture of claim 65, wherein the adjusting thegain includes adjusting a high voltage of a photomultiplier tube. 68.The article of manufacture of claim 65, wherein the adjusting the gainincludes attenuating optical signals in front of a photodetector.
 69. Anarticle of manufacture, comprising: a machine-accessible mediumincluding data that, when accessed by a machine, cause the machine toperform operations comprising, measuring parameters of spherical objectspassing through a first sample volume; determining a probability thatmore than one spherical object resides at a time in the first samplevolume is less than a predetermined threshold based on the parameters;and adjusting the aperture based on the probability.
 70. The article ofmanufacture of claim 69, wherein the determining the probabilityincludes applying a Poisson statistics.
 71. The article of manufactureof claim 69, wherein the measuring the parameters includes measuring adistance between the spherical objects.
 72. The article of manufactureof claim 69, wherein the measuring the parameters includes measuring anarrival rate of the spherical objects.
 73. An article of manufacture,comprising: a machine-accessible medium including data that, whenaccessed by a machine, cause the machine to perform operationscomprising, receiving samples of signals; measuring first parameters ofthe samples on photodetectors; estimating a first number of the samplesthat pass a first parameter validation criterion; measuring secondparameters of the samples of the signals; estimating a second number ofthe samples that pass a second parameter validation criterion; anddetermining a global measurement uncertainty based on the first numberand the second number.
 74. The article of manufacture of claim 73,wherein the first parameters include signal-to-noise ratios.
 75. Thearticle of manufacture of claim 73, wherein the second parametersinclude phases.
 76. The article of manufacture of claim 73, wherein thesecond parameters include frequencies.
 77. The article of manufacture ofclaim 73, further comprising determining a distribution of thirdparameters of the spherical objects using the global measurementuncertainty.
 78. An article of manufacture, comprising: amachine-accessible medium including data that, when accessed by amachine, cause the machine to perform operations comprising, a)receiving first signals; b) measuring first parameters of the firstsignals to characterize components of the system at an operatingcondition; c) receiving second signals; d) measuring second parametersof the second signals to characterize spherical objects; and e)adjusting the second parameters based on the first parameters.
 79. Thearticle of manufacture of claim 78, wherein the machine-accessiblemedium further includes data that cause the machine to performoperations, comprising generating a look up table based on the measuringthe first parameters at each of a plurality of operating conditions. 80.The article of manufacture of claim 78, wherein the machine-accessiblemedium further includes data that cause the machine to performoperations, comprising moving to another location; and repeatingoperations a-e.
 81. The article of manufacture of claim 78, wherein thefirst parameters include time responses of the components.
 82. Thearticle of manufacture of claim 78, wherein the second parametersinclude phases of the second signals from the spherical objects.
 83. Thearticle of manufacture of claim 78, wherein the second parametersinclude frequencies of the second signals from the spherical objects.84. The article of manufacture of claim 78, wherein the operatingcondition is a detector gain, a filter setting, a mixer setting, anoperating frequency, or any combination thereof.